Outdoor positioning systems typically cluster harvested access point (AP) signal measurements from a large number of mobile devices. Because outdoor positioning systems rely on satellite signal visibility, the clustering approach does not work indoors or in outdoor spaces where satellite signals are blocked or where the quality of satellite signals is poor due to multipath. One solution for improving outdoor localization in spaces with poor signal reception is to use indoor positioning techniques to estimate location. For example, an outdoor space, such as an “urban canyon”, is divided into a grid. The grid can be irregularly shaped and include cells that have no signal data or only sparse signal data. In this case, the grid includes a large number of radio maps, where the radio maps include “fingerprints” collected at reference locations within the outdoor space, and each fingerprint includes an identification and received signal strength of the APs observable at the reference location. Due to the high cost of cellular data service and the limited storage capacity of the typical mobile device, it is desirable to compress the radio maps before serving the radio maps to mobile devices for use in location estimation.